{"id":"W4385497738","doi":"10.1016/j.joule.2023.07.011","title":"Regeneration of direct air CO2 capture liquid via alternating electrocatalysis","year":2023,"lang":"en","type":"article","venue":"Joule","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Electrolysis; Electrocatalyst; Electrochemistry; Materials science; Electrode; Carbon dioxide; Hydrogen; Chemical engineering; Waste management; Chemistry; Environmental science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001893944,0.0003252684,0.0002808341,0.0002686004,0.0001999067,0.0004408485,0.0004316996,0.0004311029,0.001040399],"category_scores_gemma":[0.000168163,0.0001825052,0.0001728545,0.0001896959,0.0002687697,0.0005479468,0.0003893143,0.0004565052,0.0004505777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003392481,"about_ca_system_score_gemma":0.0002128482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006395911,"about_ca_topic_score_gemma":0.001809928,"domain_scores_codex":[0.9998066,0.00002234187,0.00001285868,0.00004736354,0.00005806646,0.00005280858],"domain_scores_gemma":[0.999946,0.00001678608,0.000007915455,0.000009261636,0.00001253014,0.000007583084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008593967,0.00001963744,0.00006588325,0.00004430787,0.000003727802,0.00005224932,0.00002022464,0.00005027074,0.995771,0.000246297,0.00009426617,0.003546162],"study_design_scores_gemma":[0.000005093929,0.00003565802,0.0001288334,0.00000122773,0.000002628584,0.00003251279,0.000006461105,0.0008326661,0.9981809,0.00002031547,0.0007511561,0.000002581975],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803012,0.00148856,0.01083393,0.0002166711,0.00009228259,0.00003272093,0.0001121008,0.0004372922,0.006485236],"genre_scores_gemma":[0.9938729,0.0002324649,0.002032433,0.00004477591,0.0000149602,0.00001352634,0.00007935845,0.00002562696,0.003684046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001040399,"threshold_uncertainty_score":0.003480494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009467785250367646,"score_gpt":0.2486960905553514,"score_spread":0.2392283053049838,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}